mAbs (Dec 2023)

Utility of physiologically based pharmacokinetic modeling to predict inter-antibody variability in monoclonal antibody pharmacokinetics in mice

  • Shufang Liu,
  • Sara C. Humphreys,
  • Kevin D. Cook,
  • Kip P. Conner,
  • Ana R. Correia,
  • Alex W. Jacobitz,
  • Melissa Yang,
  • Ronya Primack,
  • Marcus Soto,
  • Rupa Padaki,
  • Mariusz Lubomirski,
  • Richard Smith,
  • Marissa Mock,
  • Veena A. Thomas

DOI
https://doi.org/10.1080/19420862.2023.2263926
Journal volume & issue
Vol. 15, no. 1

Abstract

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ABSTRACTIn this investigation, we tested the hypothesis that a physiologically based pharmacokinetic (PBPK) model incorporating measured in vitro metrics of off-target binding can largely explain the inter-antibody variability in monoclonal antibody (mAb) pharmacokinetics (PK). A diverse panel of 83 mAbs was evaluated for PK in wild-type mice and subjected to 10 in vitro assays to measure major physiochemical attributes. After excluding for target-mediated elimination and immunogenicity, 56 of the remaining mAbs with an eight-fold variability in the area under the curve ([Formula: see text]: 1.74 × 106 −1.38 × 107 ng∙h/mL) and 10-fold difference in clearance (2.55–26.4 mL/day/kg) formed the training set for this investigation. Using a PBPK framework, mAb-dependent coefficients F1 and F2 modulating pinocytosis rate and convective transport, respectively, were estimated for each mAb with mostly good precision (coefficient of variation (CV%) 1. The predictive utility of the developed PBPK model was evaluated against a separate panel of 14 mAbs biased toward high clearance, among which area under the curve of PK data of 12 mAbs was predicted within 2.5-fold error, and the positive and negative predictive values for clearance prediction were 85% and 100%, respectively. MAb heparin chromatography assay output allowed a priori identification of mAb candidates with unfavorable PK.

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